Data warehouses, relational databases, and datamarts are becoming important elements of many information delivery systems because they provide a central location where a reconciled version of data extracted from a wide variety of operational systems may be stored. As used herein, a data warehouse should be understood to be an informational database that stores shareable data from one or more operational databases of record, such as one or more transaction-based database systems. A data warehouse typically allows users to tap into a business's vast store of operational data to track and respond to business trends that facilitate forecasting and planning efforts. A datamart may be considered to be a type of data warehouse that focuses on a particular business segment.
Decision support systems have been developed to efficiently retrieve selected information from data warehouses. One type of decision support system is known as an on-line analytical processing system (“OLAP”). In general, OLAP systems analyze the data from a number of different perspectives and support complex analyses against large input data sets. OLAP systems generate output upon execution of a report that includes a template to indicate the way to present the output and a filter to specify the conditions of data on which the report is to be processed.
Reports from OLAP, business intelligence or other reporting systems, may be extremely large and difficult to navigate. Additionally, common systems enable access of a report through a computer interface with limited options for presentation.
Also, reports from OLAP business intelligence or other reporting systems are useful in the way data has been processed to identify interesting trends and anomalies not apparent in raw data. However, integration of these report results with other data processing systems is not available in common systems.